Face is the most common characteristic used by humans to perform personal identity [1]}, [2]} and expression recognition [3]}. Following the emergence of the first automatic facial image analysis system in the late 1960’s [4]}, this field has attracted considerable research efforts leading to incredible progresses. Despite the recent advances in face and expression recognition, mostly thanks to the advancements in deep neural networks [5]}, [6]}, [7]}, highly accurate recognition results are still not achievable for some specific conditions. This is mostly the case when poor quality data is available, for instance due to the capture of face images in uncontrolled settings, commonly referred to as face recognition in the wild, where facial images are affected by multiple variations, notably in resolution, background, expression, pose, illumination, and occlusions, among others [8]}.
